What is CONSISTENT HASHING and Where is it used?

Рет қаралды 766,806

Күн бұрын

Load Balancing is a key concept to system design. One of the popular ways to balance load in a system is to use the concept of consistent hashing. Consistent Hashing allows requests to be mapped into hash buckets while allowing the system to add and remove nodes flexibly so as to maintain a good load factor on each machine.
The standard way to hash objects is to map them to a search space, and then transfer the load to the mapped computer. A system using this policy is likely to suffer when new nodes are added or removed from it.
Consistent Hashing maps servers to the key space and assigns requests(mapped to relevant buckets, called load) to the next clockwise server. Servers can then store relevant request data in them while allowing the system flexibility and scalability.
Some terms you would here in system design interviews are Fault Tolerance, in which case a machine crashes. And Scalability, in which case machines need to be added to process more requests. These two principles are allowed by Consistent Hashing, and hence it is an important building block to a system design architect's toolbox.
Another term used often is request allocation. This means assigning a request to a server. Consistent hashing assigns requests to the servers in a way that the load is balanced are remains close to equal.
Server architecture is a subjective concept, and there are outliers for many cases. Don't think of Consistent Hashing as a silver bullet for fault tolerance and scalability, but a useful concept for request allocation.
Use it to solve software questions in interviews and real life. Best of luck!
Prerequisite: • What is LOAD BALANCING...
Recommended system design video course:
interviewready.io
00:00 Request Hashing
03:00 Request Mapping
06:02 Problems
07:01 Virtual Servers
09:40 Applications
10:18 Thank you!
Along with video lectures, this course has architecture diagrams, capacity planning, API contracts and evaluation tests. It's a complete package.
References:
www.hackerearth.com/practice/...
www.tomkleinpeter.com/2008/03/...
michaelnielsen.org/blog/consis...
• Consistent Hashing - G...
System Design:
highscalability.com/
• What is System Design?
Code:
github.com/coding-parrot/Syst...
#consistent-hashing #system-design #load-balancing

Пікірлер: 653

@pranay020692 4 жыл бұрын

Sitting in the hotel room, watching this 1 hour before my google interview in New York. Thanks Gaurav!

@gkcs 4 жыл бұрын

All the best!

@gkcs 4 жыл бұрын

@@pranay020692 wow, tough stuff. How'd you reckon it went?

@pranay020692 4 жыл бұрын

@@gkcs I believe, It went well. I have watched most of your system design videos, they were quite helpful. I am on the junior side 3 YOE so I think they went easy on me in Sys Design. Also, I was able to complete all coding questions in time. Google is always a long shot though. 🤞🤞

@karthikmucheli7930 4 жыл бұрын

@@pranay020692 hope you got the job

@Leptoszom 3 жыл бұрын

You got the job, Bajpai?

@shreysom2060 3 жыл бұрын

I used to see your "Competitive Programming" videos before getting into a company and now after getting learning things there ,I am watching your "System Design" it feels good to grow with this channel. Thank you so much 😊

@andreimarculescu911 5 жыл бұрын

the best solution is not to use K hash functions, but to generate K replica ids for each server id. Designing K hash functions while maintaining random uniformity and consistency is hard. Generating K replica ids is easy: xxx gives K replicas xxx + '1', xxx + '2', ..., xxx + 'K'. Then you take these replicas and generate K points on the ring with the same hash function and this is what is actually used in practice. Chord algorithm is just an example of this technique to add K replicas for each server id

@gkcs 5 жыл бұрын

That makes sense. K numbers assigned to each server would do the job :)

@pradipacharjee4915 5 жыл бұрын

Hi Andrei, can you just tell me how to choose idle replica count(k) ? for efficiently add or remove servers.

@dudejaa 5 жыл бұрын

The example that you took mentions xxx+1,+2,+3...+k. Correct me if I am wrong but if you assign k consecutive numbers to the same server the load wouldn't distribute (on adding or removing a server) uniformly. That could be one reason to look for different hash functions ?

@charchitpatodi8677 5 жыл бұрын

@@dudejaa Just a thought : he probably not means +1, +2... instead if xxx is id, M is ring capacity and k is number of servers then second position (after hash(xxx) )will be hash(xxx) + (M/k) OR hash(xxx+M/k).. And probably third position will be hash(xxx) + 2*(M/k) and so on till multiple of 'k'

@rishabhmalhotra7058 5 жыл бұрын

@Abhishek Dudeja xxx, xxx+1.. are ids for one server to take a hash on and then reach the respective points on the ring, not the points on the ring itself. And then the hash generated on xxx and on xxx+1.. would be completely different and random, and hence would plot k uniformly random points. @CHARCHIT PATODI I dont think that's the case cause if you think about it , if you add multiple servers each with k different points with that technique -> hash(xxx) + 2*(M/k)..till K, then you're not really randomizing and there would be no difference between adding 1 point or k points per server when it comes to choosing a server for a request. It would be like if you multiplied the ring length into k after choosing one point per server which would not get us what we want.

@headoverbars8750 3 жыл бұрын

What an outstanding video! No shortage of tutorials on how to code or write algorithms out there buy not enough on Systems design... This is truly outstanding... been writing software 10 years and fringely do I touch these concepts, heck work within them daily yet either forgot or never knew. Thanks so much!!

@SP-db6sh Жыл бұрын

This channel is like System-Design Wala , far far better than most paid courses, simple explanation

@UlfAslak 2 жыл бұрын

Notes to self: * The previous video gives the impression that there is a mapping from ranges of integers to server ids, and that consistent hashing is about to mapping request ids to integers in ranges resulting in more consistent routing of requests to same servers. -> I did realize that this would not work very well over time, as you would end up completely changing the ranges for higher-index servers with the addition of multiple servers. * In this video, requests ids map to an index in a ring with `M` indices. The "trick" then, is the map the server indices to indices in the ring using the same hash function that also hashes request ids. Now, to assign a server to a request, one simply looks clockwise for the nearest server. * To make it less likely that load will be unbalanced due to (what I would call) unlucky hashing, another idea is used: simply have multiple hash functions for the servers, such as to map them to multiple locations in the index ring! (clever). * @Andrei Marculescu points out that better than using multiple hash functions for server ids, it is easier to maintain multiple aliases for each server id ("...xxx gives K replicas xxx + '1', xxx + '2', ..., xxx + 'K'.") and thus map servers to multiple locations in the index ring.

@Luk3Stein 2 жыл бұрын

Thank you!! I was having so much doubts after watching, reading this made it more clear.

@codingfork6708 2 жыл бұрын

How can we determine the value of `M`? Is [0, M-1] the range of the output of the hash function?

@UlfAslak 2 жыл бұрын

@@codingfork6708 Correct. I think there are good heuristics for choosing M (and probably everyone uses the same standard values). Your hash function has to apply modulus M, otherwise you get an index out of range.

@nxpy6684 Жыл бұрын

Thank you! This helped me a lot!

@timurmukhtarov1319 4 жыл бұрын

This was amazing! Havent seen other videos that talked about provisioning virtual servers/using multiple hash functions! Hooked!

@Justinkol 6 жыл бұрын

Thanks for making these videos! I was always unsure about load balancing, but this helped explain a lot of my unanswered questions :)

@gkcs 6 жыл бұрын

Glad it helped :)

@akshatagrawal3300 3 жыл бұрын

You are simply amazing gaurav, system design concepts couldn't be explained better than this!

@AbhishekKumar-ub8co 5 жыл бұрын

I loved the way with ease and simplicity you explained the problem using some pictorial diagram. Good work keep it up!!

@gkcs 5 жыл бұрын

Thank you 😋

@jeffruan7701 5 жыл бұрын

Knowledgeable and confident presenter!

@jananiravichandran8370 6 жыл бұрын

Thanks for doing this! Your videos have really helped me understand things better =)

@gkcs 6 жыл бұрын

Thanks Janani!

@raghuvamsi8740 4 жыл бұрын

After this video, I downloaded the entire playlist!! More love More support!! Gratitude _/\_

@johnleonardo 3 жыл бұрын

your content is insanely good. seriously, the best! you were destined to teach others!

@user-oy4kf5wr8l 4 жыл бұрын

u r amazing Gaurav! i watched ur video one year ago, i didnt understand then, now i watch again lol ...i understand most of it... thank u !

@harshdusane8687 5 жыл бұрын

Awesome explanation. This has truly elevated my understanding of Hashing and Load Balancing in general. Keep up the good work!!!! :)

@jrajesh11 3 жыл бұрын

Simply brilliant and clear explanation . Keep doing such awesome work.

@azeeztaiwo2802 3 жыл бұрын

best explanation of consistent hashing i have seen so far.

@asafmesika Жыл бұрын

Brilliant explanation! I read the Wikipedia article on this and Cassandra docs and your video clicked everything together!

@krishnasandeep4779 5 жыл бұрын

Your Videos are very informative. Thanks for making it Gaurav. Your explanation is crisp and Clear

@bouzie8000 4 ай бұрын

That virtual server solution blew my mind I'm so sorry. Geniuses have really paved the way for us in computer science.

@SuiMizu 5 жыл бұрын

You are a really good teacher, Gaurav! Please keep up your good work! :)

@gkcs 5 жыл бұрын

Thanks!

@arnabthakuria2243 2 жыл бұрын

Learned a lot from the actual implementation in the attached git repo . Thanks

@shishirkumar8335 5 жыл бұрын

Great video. One comment is using consistent hashing seems good option for distributed search scenarios (like you pointed for distributed cache, DB search algo) but not for use cases of load balancing where nodes are added to server large numbers of request (like web servers, applications etc). Please comment your view

@AbhishekChoudhary-tu7ig 3 жыл бұрын

I am a 3rd sem student and I guess I should not be bothering about these things but your explanations are sooooo gooood that I always wanna watch them :D

@fiveyearclub6024 5 жыл бұрын

Super helpful, thanks! I never got a CS degree and needed to learn more about sharding.

@gautamtyagi8846 3 жыл бұрын

many thanks Gaurav for making this concept so clearly explained.

@mattwilson1845 5 жыл бұрын

Awesome, thanks for making this video, really helped me understand. :D

@gkcs 5 жыл бұрын

Glad to hear that :D

@nafeezahid214 5 жыл бұрын

Excellent video Master. Thanks a lot.

@rishabhagarwal9871 5 жыл бұрын

A good video. I am really impressed. Thanks a lot.

@gymbeestar 5 жыл бұрын

This video is so helpful! Thanks!

@SayHelloMeetPatel 5 жыл бұрын

Very nice explanation. Really liked the video. Thanks. Keep making it. 👍

@gkcs 5 жыл бұрын

Thank you!

@consistentthoughts826 3 жыл бұрын

When you said try to think of solution, first thing come to my mind is "change the hash function" Thank god i'm understanding it well and its first time I am studying

@keshavabhamidipaty3126 4 жыл бұрын

Great video! I was wondering though, with this architecture, do you have to ensure that the hash functions don't ever collide though right? What would happen if an incoming request suddenly mapped to two servers that fell on the same point?

@gkcs 4 жыл бұрын

It's answered in the other comments 🙂

@krishnareddy3010 6 жыл бұрын

Wow back to back !!!

@xbeta84 4 жыл бұрын

This is great stuff!

@i-tingchen439 5 жыл бұрын

Very clear and helpful! Thank you.

@gkcs 5 жыл бұрын

Thanks!

@xiuwenzhong7375 4 жыл бұрын

thx a lot, really helpful for people like me has no sense of system design.

@responsive_random 6 жыл бұрын

Clearly explained. Thank you!

@gkcs 6 жыл бұрын

Thanks!

@jatinderarora2261 5 жыл бұрын

Thanks Gaurav. Excellent video.

@rishabhmalhotra7058 5 жыл бұрын

Awesome stuff man :)

@nankitable 4 жыл бұрын

With multiple hash being applied, can there be case of collisions, i.e. multiple servers ending up on the same bucket? If not , why? If yes, how is it handled?

@prakharsaxena796 4 жыл бұрын

Amazing videos man!!

@giobaldu 4 жыл бұрын

Great video! Question: where do the requests sit in practice? Is there a node acting as a scheduler dispatching request by request, or the requests are mapped immediately to a server and kept internally in memory? Or both, so that the requests can be rescheduled if the server goes down? (I suppose this would require the scheduler to periodically ping each server, or set a timeout). What happens if the scheduler goes down? Second question: would it be possible to use work-stealing instead do reduce inbalance? Whenever a server is out of work, it would steal a request from the back of the queue of another random server. Or could this skew too much the execution order of the requests?

@gkcs 4 жыл бұрын

Thanks! The load balancer is a service which needs to tell the other services where a request is to be routed. It can either be queried per request (which is very expensive), or a snapshot of the current assignments can be cached by all services. If the snapshot changes at the load balancer, it can notify all interested clients. The service is distributed and backed by a 'reliable' database, so a single failure won't take the system down. Second answer: It sounds complicated and I have never seen it implemented on a large scale system.

@satheeshprabhakaran5330 4 жыл бұрын

Read the article about consistent hashing in wikipedia, this video has clearly articulated the core idea. Thank you!

@hellaren 3 жыл бұрын

Thank you! It was extremely helpful

@tanvirt16 3 жыл бұрын

Gaurav, thanks so much for your videos! Very informative and easy so follow despite the complexity of the concepts. Just had a couple questions from this video! #1 So one of the original problems in the regular hashing solution was that when you add a new server, you'd have to destroy much of the local caches of the other servers because they become useless, which makes sense. So in this case, less changes occur, but how would you update the local caches to make sure you don't have to clear out the entire cache? Do you need some form of algorithm to determine what cache items should be evicted? #2 Also, how about the algorithm required to determine what the "closest" server is in the ring which will serve the request? Is there a simple mathematical solution for that, or is it somewhat complex? It does seem that the additional complexity in maintaining a consistent hashing system is worth the advantages, just want to understand a bit about how complex it actually is, or if it's simply just a genius solution to a problem.

@soumyajitdas4433 Жыл бұрын

Try looking into Chord Algorithm (en.wikipedia.org/wiki/Chord_(peer-to-peer) for #2 Tl;dr; - every node in the hash ring maintains something called a finger table containing the information around it's predecessor node, successor node and also pointer to nodes (n+2, n+4, n+8 ... n+2^k). This way we can query any node and find the successor node to a particular hash value in O(log n) time.

@osamaa.h.altameemi5592 5 жыл бұрын

fantastic explanation. Thx a ton.

@SOULOFBUU7 6 жыл бұрын

Great explanation clear and concise

@gkcs 6 жыл бұрын

Thanks!

@brothers_karamazovs Жыл бұрын

Thank you! It was clear to understand.

@deepakrao1100 5 жыл бұрын

boss code dal na ..!! studying for interviews with your videos, which btw the THE most helpful resource. Thanks for time you put into this !!!

@Arif.Amirov 4 жыл бұрын

how did your interview go?

@gkcs 4 жыл бұрын

A little late to arrive 🙈: github.com/coding-parrot/SystemDesignCourse/blob/master/service-orchestrator/src/main/java/algorithms/ConsistentHashing.java

@dacao0711 5 жыл бұрын

Thank you so much!

@gocrazy6177 5 күн бұрын

Fresher watching tiis video. Placements will start within a month

@perfectlyfantastic 4 жыл бұрын

8:33 it was told that k value should be log(M),Is it just a suggestion or its the value we should definitely consider

@roamwithashutosh 4 жыл бұрын

🙂

@eyalpery8470 2 жыл бұрын

I learned a lot, you're awesome

@SK-ur3hw 5 жыл бұрын

Great video!! I thought that we can add a load factor or load limit like one server can have x requests. So once the load limit is reached, the incoming requests will point to next clockwise server. That way, no server will have too much load. But of course the virtual servers concept is good. Can you please add the code in the desc? Thanks. :)

@gkcs 5 жыл бұрын

Sounds interesting. There are variations on consistent hashing which allow this. Code link: github.com/coding-parrot/SystemDesignCourse/blob/master/service-orchestrator/src/main/java/algorithms/ConsistentHashing.java 😁

@sreeram8942 2 жыл бұрын

@@gkcs As you said in previous video about the User's cache data in a particular server , How does consistent hashing solve that issue ?

@sridharbalabhadrapatruni1247 3 жыл бұрын

@Gaurav, What would happen to the caching that we talked about in the initial part of the discussion? I understand caching is not going to happen because the requests are too randomized for caching to occur. Is this algorithm so efficient that even without caching it's more efficient than having an algorithm that relies on caching? Also, as a performance engineer, i dealt with load balancing a few times, but never got to see these kinds of algorithms for load balancing. we have implemented algorithms that distributed load across servers based on several parameters such as - geographic proximity of the request to the server, hardware utilization (Server with least CPU, RAM, utilization gets the request), Least connections(Server serving the least active connections gets the new request), etc. Do you have anything to say about those logics, and whether they are related to the hashing algorithm we have seen...

@kaustubhparmar4274 7 ай бұрын

May be late, but I think the caching will happen because the hashes will always return the same output for same input, so if the servers do not change then caching is not affected. But if the number of server changes we need consistent hashing so as to minimise the remapping of the request to the server.

@phaneendran4208 5 жыл бұрын

Hi Gaurav, Great series of videos. Thank you for sharing your experiences. I have one question on consistent hashing.. Which component of the distributed system is responsible for implementing this technique. 1) Is it load-balancer's job because it is a load distribution technique? 2) Or is it application's responsibility.? Curious to hear your thoughts. Cheers!

@_romeopeter Жыл бұрын

I don’t know if you still need answer to this but it’s the Load Balancer’s job because distributes the request and allocate them to the right servers.

@AbhishekKumar-ky3uc 3 жыл бұрын

To be honest this video was more clear than the previos one in the playlist (what is load balancing), the pie chart concept in the previous one made me confused but this hopefully made it clear. Nice work!

@gkcs 3 жыл бұрын

Thanks!

@jeyakumar4728 4 жыл бұрын

Hi Gaurov, Wont removing / adding servers to the cluster affects the hash function modulo(%) Example: initially we have 4 servers hash(req for same id) % 4 -> s2 if we remove 1 server :- Hash(req for same id) % 3 -> s1 in this way, still the server 2 have stale cache data right?

@OmarNg7X 3 жыл бұрын

Great explanation. Thank you.

@chandrakantasaini6438 Жыл бұрын

Explain in an easy and nice way.

@romanesterkin 4 жыл бұрын

Gaurav, I have a question: if the hash function h(x) maps values to the range of (0...M-1), why do you need h(Server Number)%M? %M is redundant here, isn't it?

@vipindixit5532 9 ай бұрын

Same question from my side.

@vishalkalaskar8567 4 жыл бұрын

Hello Gaurav, when you said 'adding virtual servers' did you mean, adding differently generated hashes of the available servers so that their relative positions on hash ring is uniformly distributed giving us the flexibility of less skewed distribution of requests..? if yes, That implies if 1 physical server goes down, isn't it it's multiple hashed positions will also be off the ring giving more skewed results?

@sauravdas7591 4 жыл бұрын

Yes, it will affect the load, but consider this. If a server has, let's say, 4 points uniformly distributed across the hash ring, so when it crashes it will remove those 4 points, and this being uniformly distributed will increase the load other on other servers by 25%.

@rakeshvarma8091 3 жыл бұрын

Gaurav, This video is wonderful Have small doubts Let's assume that request R1 is served by server S1. Now we have added a new server S2. Because of this let's assume the request R1 is now coming to S2. How the above scenario gets handled ? Is it like when a new server S2 is added , we have to move some portion of the data from the existing servers (S1) to the new server S2 based on its position on the ring? If it is the case, how can we do the distribution in real time ?

@nehamadaan3328 3 жыл бұрын

@Gaurav Sen , Great Video! Thanks a lot ! Question - You mentioned at the end, its used in many many places. Are there places where systems don't use Consistent Hashing at all ? Also, are there systems using some other techniques for consistent hashing? Is this the only approach or one of the approaches to implement consistent hashing?

@gkcs 3 жыл бұрын

Yes, definitely. Consistent hashing has it's own issues, and is usually only used for servers which need to maintain state (caches). Some databases also use consistent hashing. You can also try to reduce data migration by keeping master slaves for DB servers.

@rockrock5838 3 жыл бұрын

Really well explained man....

@NehaKumari-my7cv 4 жыл бұрын

Hi Gaurav, Thanks for sharing such a nice concept.I have one doubt what happen if one server die suppose s1 for 2 hr and then again come back after that so in this case how request are handled.

@Wise___Man 3 жыл бұрын

great explanation, thanks!

@DarshitSuratwala 5 жыл бұрын

Really well explained mate. Had one question, is it the same approach used by AWS , GCP etc cloud providers?

@gkcs 5 жыл бұрын

Consistent hashing is used by many systems, so a lot of AWS users can ask for routing based on this. I think it's a customer preference.

@goutkannan 5 жыл бұрын

It is based on the load balancing logic u want to be used. One can always ask for a memcache to front any server setup

@manasdubey8667 4 жыл бұрын

Got it Gaurav, Very well explained. I am new to system designing and believe me I am enjoying it thoroughly. What I wanted to ask is, that how would you choose the value of K, to decide the number of hash functions?

@bsratuoh 11 ай бұрын

One way he told us is to use the log function with the number of servers we have. There could be another way as well.

@notthatguy1923 5 жыл бұрын

Gaurav - Awesome playlist for system design. Can you also include the explanation for when a server goes down and a request comes for a key which was saved in that server, how is the request handled? Are we going to replicate the data to not just one server but multiple servers to ensure availability. And if that is the case how to ensure consistency?

@gkcs 5 жыл бұрын

We can fail the request and retry on the newly assigned server for this request key.

@vaibhav8257 5 ай бұрын

Thank you for Teaching this in such a nice manner.😊

@xawnia 4 жыл бұрын

Thanks a lot Gaurav, this was very clear! I was wondering what would happen if there is a clash between different (or the same) hash functions h(x)=h1(y) which server will the load get assigned to?

@vikassaran6430 3 жыл бұрын

same question .....do you know the answer

@sivas09 3 жыл бұрын

'n' being the number of servers and 'm' being possible hash values, would spacing out the servers at a value of m/n be a working solution? For ex - with m as 256 and n as 4, first server could be at 64, second be at 128, third at 192 and 4 at 256 - along those lines Understood the possibility of skewed allocations and the need for replicating ids tho. Hooked to your amazing content! kudos

@yosihashamen1 3 жыл бұрын

Great explanation!

@ashutoshmishra2328 3 жыл бұрын

Hey gaurav, Thanks for this great video. i have one question, can we achieve the same results using a stick-table (which will keep user/IP and server mapping) in loadbalancer with some nondeterministic load balancing algorithm like RoundRobin or Least connection. if not then can you explain why.?

@gkcs 3 жыл бұрын

The main objective here to reduce the "rebalancing", the total number of cache loads and evictions. This is useful for load balancing on a cache cluster. The RoundRobin or Least connection algorithms are also useful in different scenarios.

@subhabera5775 4 жыл бұрын

Legendary tutorial, specially I really like where you try to prove your logicswith mathematical equations, same goes for one of the video called "finding loop in a linked list". Thanks Gaurav again :)

@kollisashank1465 6 жыл бұрын

Hi Gaurav, thanks a lot for creating these videos. It really helps us in understanding somethings which we use day to day. I have question, How do we decide on Search space M? Can we consider it as no of requests per second?

@gkcs 6 жыл бұрын

Thanks Kolli! The choice of M depends on the implementation, but it is usually a large number to have a better distribution of the hash function. Typically, values like 2^64 are used.

@SandeepVerma-yh9ec 6 жыл бұрын

Thanks, Gaurav. Nice work. I have a small doubt. As you told to handle the skewed request by having virtual servers[by having multiple hashing functions for servers], how can we handle the collisions? I mean server S1 and S2 got the same output(say O1) from the hash function. Both will be serving the user request then

@gkcs 6 жыл бұрын

That's rare. If that doesn't work, we can change one of the hash functions and rebalance 😁

@omarraghib905 Жыл бұрын

@@gkcs While hash collision might be rare, but the mod M of hashes may collide more frequently. How do we handle those?

@XYZ-nz5gm 2 жыл бұрын

You are a godsend!

@ankur2443 5 жыл бұрын

Thank you very much for explaining the concepts in such depth. I just have one question, what would happen if two different servers are hashed to same slot?

@akhilraj9334 4 жыл бұрын

Not an expert , but ideally the hash function you pick should have minimum chance of collision. Another scenario it might collide is when you are adding too many virtual servers into the ring, so should may be have a bigger ring or reduce the number of servers.

@imaginationignited7724 Жыл бұрын

What if we look for the nearest server bidirectionally? Of course if one skewed region is generated, the load between the two distant servers would be somewhat equally distributed. So what if we not only look clockwise but anticlockwise too and choose the nearest server?

@srinivasasrikanthpodila4376 3 жыл бұрын

Gaurav, The Addition/Deletion of Servers using the k-hash functions with the fixed ring size is a hard problem to solve to ensure the correctness. It could be simplified with generating the multiple ids of the same server.

@gkcs 3 жыл бұрын

That's right 👍

@sasirekhamsvl9504 2 жыл бұрын

Explained very well

@RihanPereira 5 жыл бұрын

@Gaurav sen, hashing(applying h2 function) all the servers again, will reshuffle data and request routing of all existing nodes to entirely new nodes.

@gopala5334 4 жыл бұрын

Hi Gaurav, thanks a lot for the video. I have one question, so you mean to say that the virtual servers will be mapped to available physical node? Basically a physical node, would have n number of virtual nodes of different hash functions?

@gkcs 4 жыл бұрын

Yes.

@harshulbhaliya193 2 жыл бұрын

Loved this video👾

@angadpathania 4 жыл бұрын

Hey Gaurav... Great video... I'm a non techie and was trying to get familiar with these concepts... Essentially what ur saying is as your requests increase the load balancer should have those many server allocation hash functions so that there is a higher probability of equal distribution of load... Virtual servers here basically mean having those many server hash mapped points on the ring... Am I correct..? :)

@VishalYadav-gk1kg 7 ай бұрын

Very Nice Explanation Sir, Thank you !

@ananyamathur5359 2 жыл бұрын

Hey! Thank you for your explanation. Please could you clarify my one doubt:- In a scenario where one server crashes (S4)-> it's respective k point server nodes being removed-> Now load will be distributed to the next upcoming server nodes in the Circle.. which might be say S1,S3 S1 and S2.. My question is that for all these requests blocks we would now need to configure the change of server for upcoming k nodes.. the change will be K Times .. That lands us into the same problem like your previous video. Instead it will be k times. Do let me know if I'm getting confused or this problem will happen ?

@laharibangaru3756 Жыл бұрын

same doubt 🥲could you figure out why ?

@ChandramouliMallampalli99 5 жыл бұрын

very clever solution with multiple hashes

@gkcs 5 жыл бұрын

It's super cool 😋

@AngadSingh97 9 ай бұрын

This was soooo cool!

@maitrivasa613 3 жыл бұрын

This question might have been asked before, but how do we choose the value of M for the ring? And do we increase M if the no of requests increase such that one slot in the ring can only contain either one request or one server

@sadmansakib007 3 жыл бұрын

Brilliant!!!

@Nobody2310 3 жыл бұрын

Gaurav, great explanation! thanks, when it comes to implementing this, there needs to be a directory server to store all these mappings for the keys and server points on the virtual ring, is that correct? and if yes then directory server should have replicas too in order to prevent single point failure. is my understanding correct?

@gkcs 3 жыл бұрын

I have a link for sample code in the description. For something useful in production, you have a look at ZooKeeper and how people implement consistent hashing using it. (Yes. You need to store the mappings in DB or a filesystem).

@baby_adventures 4 жыл бұрын

If we add a new server in this consistent hashing ring then again caching problem will remain same? The requests which was going through s3 before adding new server are now handle by s4.. so, s3 cache for those requests will be useless? Please explain

@mallikarjunchalla226 2 жыл бұрын

Using consistent hashing, we can overcome the rehashing problem i.e. rehashing the total number of keys which occurs in distributed hashing technique due to adding/removing servers.

@ashishmittal7048 Жыл бұрын

Thanks for the amazing video and describing the ring buffer based design for load balancing. I am wondering how this design will work efficiently when say for an example a subset of users are making too many requests? Because of consistent hashing the requests may land to the same machine , and certain machines might get more work assigned whereas all other machines are starving for the jobs.